Semi-supervised domain adaptation:
We use AlexNet[1]} and ResNet34 [2]} pre-trained on ImageNet
in all of our experiments. The architectures of feature extractor and supervised classification
head are kept the same as in [3]} for fair comparison.
For self-supervised classification head, we use a single fully-connected layer for
AlexNet, while two fully-connected layers with a ReLU activation between them is used for ResNet34. We use the
same learning rate annealing schedule as in [4]}. The model is optimized using
SGD with a momentum of 0.9 and weight decay of \(0.0005\) . The initial learning rate for feature extractor is 0.001 while for both classification heads it is 0.01.
